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  <h1>Source code for nlp_architect.procedures.transformers.seq_tag</h1><div class="highlight"><pre>
<span></span><span class="c1"># ******************************************************************************</span>
<span class="c1"># Copyright 2017-2019 Intel Corporation</span>
<span class="c1">#</span>
<span class="c1"># Licensed under the Apache License, Version 2.0 (the &quot;License&quot;);</span>
<span class="c1"># you may not use this file except in compliance with the License.</span>
<span class="c1"># You may obtain a copy of the License at</span>
<span class="c1">#</span>
<span class="c1">#     http://www.apache.org/licenses/LICENSE-2.0</span>
<span class="c1">#</span>
<span class="c1"># Unless required by applicable law or agreed to in writing, software</span>
<span class="c1"># distributed under the License is distributed on an &quot;AS IS&quot; BASIS,</span>
<span class="c1"># WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span>
<span class="c1"># See the License for the specific language governing permissions and</span>
<span class="c1"># limitations under the License.</span>
<span class="c1"># ******************************************************************************</span>
<span class="kn">import</span> <span class="nn">argparse</span>
<span class="kn">import</span> <span class="nn">io</span>
<span class="kn">import</span> <span class="nn">logging</span>
<span class="kn">import</span> <span class="nn">os</span>

<span class="kn">from</span> <span class="nn">torch.utils.data</span> <span class="kn">import</span> <span class="n">DataLoader</span><span class="p">,</span> <span class="n">RandomSampler</span><span class="p">,</span> <span class="n">SequentialSampler</span>

<span class="kn">from</span> <span class="nn">nlp_architect.data.sequential_tagging</span> <span class="kn">import</span> <span class="n">TokenClsInputExample</span><span class="p">,</span> <span class="n">TokenClsProcessor</span>
<span class="kn">from</span> <span class="nn">nlp_architect.data.utils</span> <span class="kn">import</span> <span class="n">write_column_tagged_file</span>
<span class="kn">from</span> <span class="nn">nlp_architect.models.transformers</span> <span class="kn">import</span> <span class="n">TransformerTokenClassifier</span>
<span class="kn">from</span> <span class="nn">nlp_architect.nn.torch</span> <span class="kn">import</span> <span class="n">setup_backend</span><span class="p">,</span> <span class="n">set_seed</span>
<span class="kn">from</span> <span class="nn">nlp_architect.procedures.procedure</span> <span class="kn">import</span> <span class="n">Procedure</span>
<span class="kn">from</span> <span class="nn">nlp_architect.procedures.registry</span> <span class="kn">import</span> <span class="n">register_inference_cmd</span><span class="p">,</span> <span class="n">register_train_cmd</span>
<span class="kn">from</span> <span class="nn">nlp_architect.procedures.transformers.base</span> <span class="kn">import</span> <span class="n">create_base_args</span><span class="p">,</span> <span class="n">inference_args</span><span class="p">,</span> <span class="n">train_args</span>
<span class="kn">from</span> <span class="nn">nlp_architect.utils.io</span> <span class="kn">import</span> <span class="n">prepare_output_path</span>
<span class="kn">from</span> <span class="nn">nlp_architect.utils.text</span> <span class="kn">import</span> <span class="n">SpacyInstance</span>

<span class="n">logger</span> <span class="o">=</span> <span class="n">logging</span><span class="o">.</span><span class="n">getLogger</span><span class="p">(</span><span class="vm">__name__</span><span class="p">)</span>


<div class="viewcode-block" id="TransformerTokenClsTrain"><a class="viewcode-back" href="../../../../generated_api/nlp_architect.procedures.transformers.html#nlp_architect.procedures.transformers.seq_tag.TransformerTokenClsTrain">[docs]</a><span class="nd">@register_train_cmd</span><span class="p">(</span>
    <span class="n">name</span><span class="o">=</span><span class="s2">&quot;transformer_token&quot;</span><span class="p">,</span> <span class="n">description</span><span class="o">=</span><span class="s2">&quot;Train a BERT/XLNet model with token classification head&quot;</span>
<span class="p">)</span>
<span class="k">class</span> <span class="nc">TransformerTokenClsTrain</span><span class="p">(</span><span class="n">Procedure</span><span class="p">):</span>
<div class="viewcode-block" id="TransformerTokenClsTrain.add_arguments"><a class="viewcode-back" href="../../../../generated_api/nlp_architect.procedures.transformers.html#nlp_architect.procedures.transformers.seq_tag.TransformerTokenClsTrain.add_arguments">[docs]</a>    <span class="nd">@staticmethod</span>
    <span class="k">def</span> <span class="nf">add_arguments</span><span class="p">(</span><span class="n">parser</span><span class="p">:</span> <span class="n">argparse</span><span class="o">.</span><span class="n">ArgumentParser</span><span class="p">):</span>
        <span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span>
            <span class="s2">&quot;--data_dir&quot;</span><span class="p">,</span>
            <span class="n">default</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
            <span class="nb">type</span><span class="o">=</span><span class="nb">str</span><span class="p">,</span>
            <span class="n">required</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
            <span class="n">help</span><span class="o">=</span><span class="s2">&quot;The input data dir. Should contain dataset files to be parsed &quot;</span>
            <span class="o">+</span> <span class="s2">&quot;by the dataloaders.&quot;</span><span class="p">,</span>
        <span class="p">)</span>
        <span class="n">train_args</span><span class="p">(</span><span class="n">parser</span><span class="p">,</span> <span class="n">models_family</span><span class="o">=</span><span class="n">TransformerTokenClassifier</span><span class="o">.</span><span class="n">MODEL_CLASS</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
        <span class="n">create_base_args</span><span class="p">(</span><span class="n">parser</span><span class="p">,</span> <span class="n">model_types</span><span class="o">=</span><span class="n">TransformerTokenClassifier</span><span class="o">.</span><span class="n">MODEL_CLASS</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
        <span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span>
            <span class="s2">&quot;--train_file_name&quot;</span><span class="p">,</span>
            <span class="nb">type</span><span class="o">=</span><span class="nb">str</span><span class="p">,</span>
            <span class="n">default</span><span class="o">=</span><span class="s2">&quot;train.txt&quot;</span><span class="p">,</span>
            <span class="n">help</span><span class="o">=</span><span class="s2">&quot;File name of the training dataset&quot;</span><span class="p">,</span>
        <span class="p">)</span></div>

<div class="viewcode-block" id="TransformerTokenClsTrain.run_procedure"><a class="viewcode-back" href="../../../../generated_api/nlp_architect.procedures.transformers.html#nlp_architect.procedures.transformers.seq_tag.TransformerTokenClsTrain.run_procedure">[docs]</a>    <span class="nd">@staticmethod</span>
    <span class="k">def</span> <span class="nf">run_procedure</span><span class="p">(</span><span class="n">args</span><span class="p">):</span>
        <span class="n">do_training</span><span class="p">(</span><span class="n">args</span><span class="p">)</span></div></div>


<div class="viewcode-block" id="TransformerTokenClsRun"><a class="viewcode-back" href="../../../../generated_api/nlp_architect.procedures.transformers.html#nlp_architect.procedures.transformers.seq_tag.TransformerTokenClsRun">[docs]</a><span class="nd">@register_inference_cmd</span><span class="p">(</span>
    <span class="n">name</span><span class="o">=</span><span class="s2">&quot;transformer_token&quot;</span><span class="p">,</span> <span class="n">description</span><span class="o">=</span><span class="s2">&quot;Run a BERT/XLNet model with token classification head&quot;</span>
<span class="p">)</span>
<span class="k">class</span> <span class="nc">TransformerTokenClsRun</span><span class="p">(</span><span class="n">Procedure</span><span class="p">):</span>
<div class="viewcode-block" id="TransformerTokenClsRun.add_arguments"><a class="viewcode-back" href="../../../../generated_api/nlp_architect.procedures.transformers.html#nlp_architect.procedures.transformers.seq_tag.TransformerTokenClsRun.add_arguments">[docs]</a>    <span class="nd">@staticmethod</span>
    <span class="k">def</span> <span class="nf">add_arguments</span><span class="p">(</span><span class="n">parser</span><span class="p">:</span> <span class="n">argparse</span><span class="o">.</span><span class="n">ArgumentParser</span><span class="p">):</span>
        <span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span>
            <span class="s2">&quot;--data_file&quot;</span><span class="p">,</span>
            <span class="n">default</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
            <span class="nb">type</span><span class="o">=</span><span class="nb">str</span><span class="p">,</span>
            <span class="n">required</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
            <span class="n">help</span><span class="o">=</span><span class="s2">&quot;The data file containing data for inference&quot;</span><span class="p">,</span>
        <span class="p">)</span>
        <span class="n">inference_args</span><span class="p">(</span><span class="n">parser</span><span class="p">)</span>
        <span class="n">create_base_args</span><span class="p">(</span><span class="n">parser</span><span class="p">,</span> <span class="n">model_types</span><span class="o">=</span><span class="n">TransformerTokenClassifier</span><span class="o">.</span><span class="n">MODEL_CLASS</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span></div>

<div class="viewcode-block" id="TransformerTokenClsRun.run_procedure"><a class="viewcode-back" href="../../../../generated_api/nlp_architect.procedures.transformers.html#nlp_architect.procedures.transformers.seq_tag.TransformerTokenClsRun.run_procedure">[docs]</a>    <span class="nd">@staticmethod</span>
    <span class="k">def</span> <span class="nf">run_procedure</span><span class="p">(</span><span class="n">args</span><span class="p">):</span>
        <span class="n">do_inference</span><span class="p">(</span><span class="n">args</span><span class="p">)</span></div></div>


<div class="viewcode-block" id="do_training"><a class="viewcode-back" href="../../../../generated_api/nlp_architect.procedures.transformers.html#nlp_architect.procedures.transformers.seq_tag.do_training">[docs]</a><span class="k">def</span> <span class="nf">do_training</span><span class="p">(</span><span class="n">args</span><span class="p">):</span>
    <span class="n">prepare_output_path</span><span class="p">(</span><span class="n">args</span><span class="o">.</span><span class="n">output_dir</span><span class="p">,</span> <span class="n">args</span><span class="o">.</span><span class="n">overwrite_output_dir</span><span class="p">)</span>
    <span class="n">device</span><span class="p">,</span> <span class="n">n_gpus</span> <span class="o">=</span> <span class="n">setup_backend</span><span class="p">(</span><span class="n">args</span><span class="o">.</span><span class="n">no_cuda</span><span class="p">)</span>
    <span class="c1"># Set seed</span>
    <span class="n">args</span><span class="o">.</span><span class="n">seed</span> <span class="o">=</span> <span class="n">set_seed</span><span class="p">(</span><span class="n">args</span><span class="o">.</span><span class="n">seed</span><span class="p">,</span> <span class="n">n_gpus</span><span class="p">)</span>
    <span class="c1"># prepare data</span>
    <span class="n">processor</span> <span class="o">=</span> <span class="n">TokenClsProcessor</span><span class="p">(</span><span class="n">args</span><span class="o">.</span><span class="n">data_dir</span><span class="p">)</span>

    <span class="n">classifier</span> <span class="o">=</span> <span class="n">TransformerTokenClassifier</span><span class="p">(</span>
        <span class="n">model_type</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">model_type</span><span class="p">,</span>
        <span class="n">model_name_or_path</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">model_name_or_path</span><span class="p">,</span>
        <span class="n">labels</span><span class="o">=</span><span class="n">processor</span><span class="o">.</span><span class="n">get_labels</span><span class="p">(),</span>
        <span class="n">config_name</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">config_name</span><span class="p">,</span>
        <span class="n">tokenizer_name</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">tokenizer_name</span><span class="p">,</span>
        <span class="n">do_lower_case</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">do_lower_case</span><span class="p">,</span>
        <span class="n">output_path</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">output_dir</span><span class="p">,</span>
        <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">,</span>
        <span class="n">n_gpus</span><span class="o">=</span><span class="n">n_gpus</span><span class="p">,</span>
    <span class="p">)</span>

    <span class="n">train_ex</span> <span class="o">=</span> <span class="n">processor</span><span class="o">.</span><span class="n">get_train_examples</span><span class="p">(</span><span class="n">filename</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">train_file_name</span><span class="p">)</span>
    <span class="k">if</span> <span class="n">train_ex</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
        <span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">&quot;No train examples found, quitting.&quot;</span><span class="p">)</span>
    <span class="n">dev_ex</span> <span class="o">=</span> <span class="n">processor</span><span class="o">.</span><span class="n">get_dev_examples</span><span class="p">()</span>
    <span class="n">test_ex</span> <span class="o">=</span> <span class="n">processor</span><span class="o">.</span><span class="n">get_test_examples</span><span class="p">()</span>

    <span class="n">train_batch_size</span> <span class="o">=</span> <span class="n">args</span><span class="o">.</span><span class="n">per_gpu_train_batch_size</span> <span class="o">*</span> <span class="nb">max</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">n_gpus</span><span class="p">)</span>

    <span class="n">train_dataset</span> <span class="o">=</span> <span class="n">classifier</span><span class="o">.</span><span class="n">convert_to_tensors</span><span class="p">(</span><span class="n">train_ex</span><span class="p">,</span> <span class="n">max_seq_length</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">max_seq_length</span><span class="p">)</span>
    <span class="n">train_sampler</span> <span class="o">=</span> <span class="n">RandomSampler</span><span class="p">(</span><span class="n">train_dataset</span><span class="p">)</span>
    <span class="n">train_dl</span> <span class="o">=</span> <span class="n">DataLoader</span><span class="p">(</span><span class="n">train_dataset</span><span class="p">,</span> <span class="n">sampler</span><span class="o">=</span><span class="n">train_sampler</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">train_batch_size</span><span class="p">)</span>
    <span class="n">dev_dl</span> <span class="o">=</span> <span class="kc">None</span>
    <span class="n">test_dl</span> <span class="o">=</span> <span class="kc">None</span>
    <span class="k">if</span> <span class="n">dev_ex</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
        <span class="n">dev_dataset</span> <span class="o">=</span> <span class="n">classifier</span><span class="o">.</span><span class="n">convert_to_tensors</span><span class="p">(</span><span class="n">dev_ex</span><span class="p">,</span> <span class="n">max_seq_length</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">max_seq_length</span><span class="p">)</span>
        <span class="n">dev_sampler</span> <span class="o">=</span> <span class="n">SequentialSampler</span><span class="p">(</span><span class="n">dev_dataset</span><span class="p">)</span>
        <span class="n">dev_dl</span> <span class="o">=</span> <span class="n">DataLoader</span><span class="p">(</span>
            <span class="n">dev_dataset</span><span class="p">,</span> <span class="n">sampler</span><span class="o">=</span><span class="n">dev_sampler</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">per_gpu_eval_batch_size</span>
        <span class="p">)</span>

    <span class="k">if</span> <span class="n">test_ex</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
        <span class="n">test_dataset</span> <span class="o">=</span> <span class="n">classifier</span><span class="o">.</span><span class="n">convert_to_tensors</span><span class="p">(</span><span class="n">test_ex</span><span class="p">,</span> <span class="n">max_seq_length</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">max_seq_length</span><span class="p">)</span>
        <span class="n">test_sampler</span> <span class="o">=</span> <span class="n">SequentialSampler</span><span class="p">(</span><span class="n">test_dataset</span><span class="p">)</span>
        <span class="n">test_dl</span> <span class="o">=</span> <span class="n">DataLoader</span><span class="p">(</span>
            <span class="n">test_dataset</span><span class="p">,</span> <span class="n">sampler</span><span class="o">=</span><span class="n">test_sampler</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">per_gpu_eval_batch_size</span>
        <span class="p">)</span>

    <span class="n">total_steps</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">classifier</span><span class="o">.</span><span class="n">get_train_steps_epochs</span><span class="p">(</span>
        <span class="n">args</span><span class="o">.</span><span class="n">max_steps</span><span class="p">,</span> <span class="n">args</span><span class="o">.</span><span class="n">num_train_epochs</span><span class="p">,</span> <span class="n">args</span><span class="o">.</span><span class="n">per_gpu_train_batch_size</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">train_dataset</span><span class="p">)</span>
    <span class="p">)</span>

    <span class="n">classifier</span><span class="o">.</span><span class="n">setup_default_optimizer</span><span class="p">(</span>
        <span class="n">weight_decay</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">weight_decay</span><span class="p">,</span>
        <span class="n">learning_rate</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">learning_rate</span><span class="p">,</span>
        <span class="n">adam_epsilon</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">adam_epsilon</span><span class="p">,</span>
        <span class="n">warmup_steps</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">warmup_steps</span><span class="p">,</span>
        <span class="n">total_steps</span><span class="o">=</span><span class="n">total_steps</span><span class="p">,</span>
    <span class="p">)</span>
    <span class="n">classifier</span><span class="o">.</span><span class="n">train</span><span class="p">(</span>
        <span class="n">train_dl</span><span class="p">,</span>
        <span class="n">dev_dl</span><span class="p">,</span>
        <span class="n">test_dl</span><span class="p">,</span>
        <span class="n">gradient_accumulation_steps</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">gradient_accumulation_steps</span><span class="p">,</span>
        <span class="n">per_gpu_train_batch_size</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">per_gpu_train_batch_size</span><span class="p">,</span>
        <span class="n">max_steps</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">max_steps</span><span class="p">,</span>
        <span class="n">num_train_epochs</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">num_train_epochs</span><span class="p">,</span>
        <span class="n">max_grad_norm</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">max_grad_norm</span><span class="p">,</span>
        <span class="n">logging_steps</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">logging_steps</span><span class="p">,</span>
        <span class="n">save_steps</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">save_steps</span><span class="p">,</span>
    <span class="p">)</span>
    <span class="n">classifier</span><span class="o">.</span><span class="n">save_model</span><span class="p">(</span><span class="n">args</span><span class="o">.</span><span class="n">output_dir</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="n">args</span><span class="p">)</span></div>


<div class="viewcode-block" id="do_inference"><a class="viewcode-back" href="../../../../generated_api/nlp_architect.procedures.transformers.html#nlp_architect.procedures.transformers.seq_tag.do_inference">[docs]</a><span class="k">def</span> <span class="nf">do_inference</span><span class="p">(</span><span class="n">args</span><span class="p">):</span>
    <span class="n">prepare_output_path</span><span class="p">(</span><span class="n">args</span><span class="o">.</span><span class="n">output_dir</span><span class="p">,</span> <span class="n">args</span><span class="o">.</span><span class="n">overwrite_output_dir</span><span class="p">)</span>
    <span class="n">device</span><span class="p">,</span> <span class="n">n_gpus</span> <span class="o">=</span> <span class="n">setup_backend</span><span class="p">(</span><span class="n">args</span><span class="o">.</span><span class="n">no_cuda</span><span class="p">)</span>
    <span class="n">args</span><span class="o">.</span><span class="n">batch_size</span> <span class="o">=</span> <span class="n">args</span><span class="o">.</span><span class="n">per_gpu_eval_batch_size</span> <span class="o">*</span> <span class="nb">max</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">n_gpus</span><span class="p">)</span>
    <span class="n">inference_examples</span> <span class="o">=</span> <span class="n">process_inference_input</span><span class="p">(</span><span class="n">args</span><span class="o">.</span><span class="n">data_file</span><span class="p">)</span>
    <span class="n">classifier</span> <span class="o">=</span> <span class="n">TransformerTokenClassifier</span><span class="o">.</span><span class="n">load_model</span><span class="p">(</span>
        <span class="n">model_path</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">model_path</span><span class="p">,</span>
        <span class="n">model_type</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">model_type</span><span class="p">,</span>
        <span class="n">do_lower_case</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">do_lower_case</span><span class="p">,</span>
        <span class="n">load_quantized</span><span class="o">=</span><span class="n">args</span><span class="o">.</span><span class="n">load_quantized_model</span><span class="p">,</span>
    <span class="p">)</span>
    <span class="n">classifier</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="n">n_gpus</span><span class="p">)</span>
    <span class="n">output</span> <span class="o">=</span> <span class="n">classifier</span><span class="o">.</span><span class="n">inference</span><span class="p">(</span><span class="n">inference_examples</span><span class="p">,</span> <span class="n">args</span><span class="o">.</span><span class="n">max_seq_length</span><span class="p">,</span> <span class="n">args</span><span class="o">.</span><span class="n">batch_size</span><span class="p">)</span>
    <span class="n">write_column_tagged_file</span><span class="p">(</span><span class="n">args</span><span class="o">.</span><span class="n">output_dir</span> <span class="o">+</span> <span class="n">os</span><span class="o">.</span><span class="n">sep</span> <span class="o">+</span> <span class="s2">&quot;output.txt&quot;</span><span class="p">,</span> <span class="n">output</span><span class="p">)</span></div>


<div class="viewcode-block" id="process_inference_input"><a class="viewcode-back" href="../../../../generated_api/nlp_architect.procedures.transformers.html#nlp_architect.procedures.transformers.seq_tag.process_inference_input">[docs]</a><span class="k">def</span> <span class="nf">process_inference_input</span><span class="p">(</span><span class="n">input_file</span><span class="p">):</span>
    <span class="k">with</span> <span class="n">io</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">input_file</span><span class="p">)</span> <span class="k">as</span> <span class="n">fp</span><span class="p">:</span>
        <span class="n">texts</span> <span class="o">=</span> <span class="p">[</span><span class="n">l</span><span class="o">.</span><span class="n">strip</span><span class="p">()</span> <span class="k">for</span> <span class="n">l</span> <span class="ow">in</span> <span class="n">fp</span><span class="o">.</span><span class="n">readlines</span><span class="p">()]</span>
    <span class="n">tokenizer</span> <span class="o">=</span> <span class="n">SpacyInstance</span><span class="p">(</span><span class="n">disable</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;tagger&quot;</span><span class="p">,</span> <span class="s2">&quot;parser&quot;</span><span class="p">,</span> <span class="s2">&quot;ner&quot;</span><span class="p">])</span>
    <span class="n">examples</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">t</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">texts</span><span class="p">):</span>
        <span class="n">examples</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">TokenClsInputExample</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">i</span><span class="p">),</span> <span class="n">t</span><span class="p">,</span> <span class="n">tokenizer</span><span class="o">.</span><span class="n">tokenize</span><span class="p">(</span><span class="n">t</span><span class="p">)))</span>
    <span class="k">return</span> <span class="n">examples</span></div>
</pre></div>

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